Vehicle parameters identification with particle swarm optimisation for four wheel independent motor-drive vehicle Online publication date: Thu, 19-Sep-2019
by Hongliang Zhou; Zhiyuang Liu; Xingwang Yang; Levent Güvenç
International Journal of Vehicle Design (IJVD), Vol. 79, No. 2/3, 2019
Abstract: An identification method for vehicle dynamics parameters which is based on particle swarm optimisation (PSO) is presented in this paper for a four wheel independent motor-drive (4WIMD) vehicle. The identification process consists of two steps. In the first step, wheel rotational dynamic and static resistance coefficients are identified using field test data of motor torque and wheel speed. In the second step, a nonlinear vehicle dynamics model with vehicle longitudinal and lateral dynamics, wheel dynamics model and tyre characteristics, and the parameters related to vehicle body and the tyre are identified with the test data of motor torque, accelerations, yaw rate and wheel speeds. The model outputs and test data are compared and the parameters show acceptable accuracy. A benchmarking study using a commercially available optimisation routine for the same parameter identification task is carried out and the PSD method presented here is observed to be much more accurate.
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